scholarly journals Intensification of Azo Dye Removal Rate in the Presence of Immobilized Nanoparticles and Inorganic Anions under UV-C Irradiation: Optimization by Response Surface Methodology

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Mohammad A. Behnajady ◽  
Mahsa Hajiahmadi
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Azo Dye ◽  
Dye Removal ◽  
Removal Rate ◽  
Organic Pollutant ◽  
Inorganic Anions ◽  
Coefficient Of Determination ◽  
Synergy Effect ◽  
Uv C

Wastewaters contain inorganic anions that affect the removal rate of organic pollutants. The present study aims to optimize the effects of inorganic anions such as , Cl−, , and on the removal rate of an organic pollutant in the presence of immobilized TiO2nanoparticles using response surface methodology (RSM). C.I. Acid Red 17 (AR17) was used as a model organic pollutant. Thirty experiments were required to study the effects of anions in various concentrations. The results indicate that the addition of and ions intensifies the removal rate of AR17. The results of the analysis of variance (ANOVA) showed a high coefficient of determination value ( and ). The results indicate that RSM is a suitable method for modeling and optimizing the process. The results prove that in the presence of and and ions especially in the combination situation the removal rate of AR17 is enhanced considerably. An important synergy effect was observed in the combination of and ions, so that AR17 removal percent under the optimized RSM conditions was considerably more than the sum of removal percent when these ions are used individually.

scholarly journals Adsorption of Remazol Brillant Green 6B (RBG 6B) on chitin: process optimization using response surface methodology

2018 ◽  
Vol 20 (2) ◽  
pp. 257-268 ◽  
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Removal Efficiency ◽  
Dye Removal ◽  
Freundlich Isotherm ◽  
Sem Analysis ◽  
Second Order ◽  
Operating Conditions ◽  
Coefficient Of Determination ◽  
Solution Ph

In the present study, the adsorption of Remazol Brillant Green 6B (RBG 6B) on chitin which characterized by BET, FTIR, XRD and SEM analysis was studied. Response surface methodology (RSM) was applied to determine interaction between solution pH, initial RBG 6B concentration and chitin dosage being individual variables and to optimize operating conditions. According to results of variance analysis (ANOVA), the second order polynomial model was statistically significant (P<0.0001) and coefficient of determination value (R2=0.98) was high. It was determined that dye removal efficiency increased when low solution pH and initial RBG 6B dye concentration and high chitin dosage were used. The maximum dye removal efficiency was obtained as 88% at solution pH of 3.0, initial RBG 6B concentration of 75 mg L-1 and chitin dosage of 5.0 g L-1. The isotherms and kinetics studies showed that Freundlich isotherm and pseudo-second-order kinetics model fitted well to the RBG 6B adsorption data.

scholarly journals Comparative Prediction of Red Alga Biosorbent Performance in Dye Removal using Multivariate Models of Response Surface Methodology (RSM) and Artificial Neural Network (ANN)

2018 ◽  
Vol 7 (4.35) ◽  
pp. 551
Author(s):  
Nadiah Mokhtar ◽  
Edriyana A.Aziz ◽  
Azmi Aris ◽  
W.FW. Ishak ◽  
Anwar P.P. Abdul Majeed ◽  
...  
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Dye Removal ◽  
Removal Rate ◽  
Desirability Function ◽  
Quadratic Model ◽  
Ann Model ◽  
Biosorption Process ◽  
Rsm Model ◽  
High Removal Rate

Red algae species, Euchema Spinosum (ES) in Malaysia possesses excellent biosorbent properties in removing dyes from aqueous solutions. In the present study, the experimental design for the biosorption process was carried out via response surface methodology (RSM-CCD). A total of 20 runs were carried out to generate a quadratic model and further analysed for optimisation. Prior to the evaluation, the characterisation study of the ES was performed. It was observed that the maximum uptake capacity of 399 mg/g (>95%) is obtained at equilibrium time of 60 min, pH solution of 6.9-7.1, dosage of 0.72 g/L and initial dye concentration of 300 g/L through statistical optimisation (CCD-RSM) based on the desirability function. It is demonstrated in the present study that the ANN model (R2=0.9994, adj-R2=0.9916, MSE=0.19, RMSE=0.4391, MAPE=0.087 and AARE=0.001) is able to provide a slightly better prediction in comparison to the RSM model (R2= 0.9992, adj-R2= 0.9841, MSE=1.95, RMSE=1.395, MAPE=0.08 and AARE=0.001). Moreover, the SEM-EDX analysis indicates the development of a considerable number of pore size ranging between 132 to 175 mm. From the experimental observations, it is evident that the ES can achieve high removal rate (>95%), indeed become a promising eco-friendly biosorptive material for MB dye removal.

Quantification of tool chatter and metal removal rate using wavelet denoising and statistical approach

2018 ◽  
Vol 49 (2) ◽  
pp. 62-81 ◽  
Author(s):  
Shailendra Kumar ◽  
Bhagat Singh
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Metal Removal ◽  
Removal Rate ◽  
Statistical Significance ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Metal Removal Rate ◽  
Chatter Index ◽  
Tool Chatter

Tool chatter is an unavoidable phenomenon encountered in machining processes. Acquired raw chatter signals are contaminated with various types of ambient noises. Signal processing is an efficient technique to explore chatter as it eliminates unwanted background noise present in the raw signal. In this study, experimentally recorded raw chatter signals have been denoised using wavelet transform in order to eliminate the unwanted noise inclusions. Moreover, effect of machining parameters such as depth of cut ( d), feed rate ( f) and spindle speed ( N) on chatter severity and metal removal rate has been ascertained experimentally. Furthermore, in order to quantify the chatter severity, a new parameter called chatter index has been evaluated considering aforesaid denoised signals. A set of 15 experimental runs have been performed using Box–Behnken design of experiment. These experimental observations have been used to develop mathematical models for chatter index and metal removal rate considering response surface methodology. In order to check the statistical significance of control parameters, analysis of variance has been performed. Furthermore, more experiments are conducted and these results are compared with the theoretical ones in order to validate the developed response surface methodology model.

scholarly journals Optimization of Crude Oil and PAHs Degradation by Stenotrophomonas rhizophila KX082814 Strain through Response Surface Methodology Using Box-Behnken Design

2016 ◽  
Vol 2016 ◽  
pp. 1-13 ◽  
Author(s):  
Praveen Kumar Siddalingappa Virupakshappa ◽  
Manjunatha Bukkambudhi Krishnaswamy ◽  
Gaurav Mishra ◽  
Mohammed Ameenuddin Mehkri
Keyword(s):  
Response Surface Methodology ◽  
Crude Oil ◽  
Response Surface ◽  
Oxygen Demand ◽  
Inoculum Size ◽  
Coefficient Of Determination ◽  
Oil Removal ◽  
Box Behnken Design ◽  
Stenotrophomonas Rhizophila ◽  
Crude Oil Removal

The present paper describes the process optimization study for crude oil degradation which is a continuation of our earlier work on hydrocarbon degradation study of the isolate Stenotrophomonas rhizophila (PM-1) with GenBank accession number KX082814. Response Surface Methodology with Box-Behnken Design was used to optimize the process wherein temperature, pH, salinity, and inoculum size (at three levels) were used as independent variables and Total Petroleum Hydrocarbon, Biological Oxygen Demand, and Chemical Oxygen Demand of crude oil and PAHs as dependent variables (response). The statistical analysis, via ANOVA, showed coefficient of determination R2 as 0.7678 with statistically significant P value 0.0163 fitting in second-order quadratic regression model for crude oil removal. The predicted optimum parameters, namely, temperature, pH, salinity, and inoculum size, were found to be 32.5°C, 9, 12.5, and 12.5 mL, respectively. At this optimum condition, the observed and predicted PAHs and crude oil removal were found to be 71.82% and 79.53% in validation experiments, respectively. The % TPH results correlate with GC/MS studies, BOD, COD, and TPC. The validation of numerical optimization was done through GC/MS studies and   % removal of crude oil.

Sign in / Sign up

Export Citation Format

Share Document